Geospatial Auto-Correlation Statistical Analysis to Evaluate the Seismic Magnitudes and Its Implications on the Mediterranean Coastal Zone of Egypt

Physical Science International Journal

20(3): 1-15, 2018; Article no.PSIJ.46208 ISSN: 2348-0130

Geospatial Auto-correlation Statistical Analysis to Evaluate the Seismic Magnitudes and Its Implications on the Mediterranean Coastal Zone of Egypt

Ali Amasha1*, Islam Abou El-Magd2 and Elham Ali3

1Arab Academy for Science, Technology & Maritime Transport, Complex, Block 1167, Off El-Moshir Ahmed Ismail St., P.O.Box 2033 – El-Horria, Cairo, Egypt. 2National authority for Remote Sensing and Space Sciences, 23 Josef Tito St., El-Nozaha El-Gedida, P.O.Box 1564, Cairo, Egypt. 3Suez University, University Road, Suez, Egypt.

Authors’ contributions

This work was carried out in collaboration between all authors. Author AA has designed the study, performed and managed the statistical analysis, wrote the protocol, wrote the first draft of the manuscript and managed the submission to the journal. All authors AA, IAEM and EA have managed the literature searches, shared in writing the manuscript and read and approved the final manuscript.

Article Information

DOI: 10.9734/PSIJ/2018/46208 Editor(s): (1) Dr. David G. Yurth, Director of Science & Technology, The Nova Institute of Technology Holladay, Utah, USA. (2) Dr. Roberto Oscar Aquilano, School of Exact Science, National University of Rosario (UNR), Rosario, Physics Institute (IFIR)(CONICET-UNR), Argentina. Reviewers: (1) Agu Eensaar, Tallinn University of Applied Sciences, Estonia. (2) Jūratė Sužiedelytė Visockienė, Vilnius Gediminas Technical University, Lithuania. Complete Peer review History: http://www.sciencedomain.org/review-history/28142

Received 07 October 2018 Original Research Article Accepted 26 December 2018 Published 05 January 2019

ABSTRACT

The northern coastal zone of Egypt (Mediterranean) is under the force of tension shear zones of African and European plates that generate earthquakes with variable magnitudes. We try to find a spatial relation between the collected seismic points and to evaluate how much these points affect and accelerate the frequencies of the high magnitudes’ earthquakes events. Geospatial and statistical analyses (e.g. ArcGIS tools) have used to analyze nearly 3083 earthquake records in the last 65 years in the Mediterranean basin in relation to the geo-tectonic shear zones. Nearly 85% of these earthquakes were in the marine. Aegean and Anatolia shear zones are the highest contributors of the earthquakes with nearly 43% and 42% respectively. Three results of the ______

*Corresponding author: E-mail: [email protected], [email protected];

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

dominant geotectonic hazards were obtained. The first is that the majority of the hot spotted earthquakes are located at the Aegean Sea which enforcing the frequency and severity of earthquakes and tsunamis than that of Anatolia plate. The northward movement rate towards the African-Aegean plate is a bit lower due to the existing of the Mediterranean ridge and Strabo and Pliny trenches which resisting the African plate northward subduction. The second is that the subsidence rates and directions at the coastal Nile delta region is aligned to the rates and directions of the tectonic plates’ movements and the compaction rates of the deltaic sediments. The third is that the depths of the majority earthquakes epicenters (85%) were down to 40 km from the sea floor, one third of them were within the shallower 10 km depth. These results approve the frequencies of the severe earthquakes are potential based on the spatial statistical analysis. Therefore, the Egyptian coastal zone is vulnerability-marked where a lot of developmental activities were located.

Keywords: Geospatial analysis; geo-tectonic hazards; coastal-zone; Nile-Delta; Egypt.

1. INTRODUCTION In the context local spatial autocorrelation indices, we used the geo-statistical tools to evaluate the Natural disasters cause significant financial spatial relations between the seismic point’s pressure, on government and individuals, with locations and their magnitudes’ values. The local short-term impacts and wider long-term analysis methods of local Getis–Ord Gi statistics development implications. Vulnerability to were used to evaluate spatial patterns of earthquakes hazards is shifting quickly, especially distribution of seismic magnitudes values by in developing countries with rapid population considering both their locations and associate growth, urbanization and socio-economic correlation values. This method uses a measure transformational changes. Coastal zones are known as the spatial autocorrelation coefficient to known to be the most vulnerable to natural and measure and test how observed locations are environmental hazards due to the physical clustered/dispersed in space with respect to characteristics of the high flood probability, the correlation values. The spatial autocorrelation at low topography, and the high sensitivity to the local scale, it is necessary to calculate local climatic changes, [1]. However, the deltaic autocorrelation indices like Getis–Ord Gi environment i s wealthy with natural resources statistics, [7]. that often support large populations, [2]. The Hot Spot Analysis by calculating Getis–Ord Earthquakes occur in the crust or upper mantle, Gi statistics was performed in order to obtain which ranges from the earth's surface to about more insight into how the stations with high and 800 kilometers deep (about 500 miles). However, low levels of calculated correlation coefficients shaking strength from an earthquake diminishes are clustered. A high positive Z-score of Gi with increasing distance from the earthquake's statistics appears when the spatial clustering is source, [3]. Depths of earthquakes can give us formed by similar but high values, the larger the Z important information about the Earth's structure score the more intense the clustering of high and the tectonic setting where the earthquakes values. If the spatial clustering is formed by low are occurring, [4]. Within continents, and along values, the Z-score will tend to be highly negative continental plate boundary transform faults, faults and the smaller the Z score is the more intense are only active in the shallow crust (i.e. to depths the clustering of low values. A Z-score around 0 of approximately 20 km). Globally, between indicates no apparent spatial association pattern, 1950-1999, earthquakes constituted 29% of [8]. great natural catastrophes, with 47% of the fatalities, 35% of economic losses and 18% of In addition, we used other geo-statistical module insured losses, [5]. of the ArcGIS to compare and approve the auto- correlated values. Anselin Moran’s I represents Whereas, the northern coastal zone of the measure of autocorrelation values that given Egypt is highly dynamic zone with various socio- in spatial context, [9]. Incremental Spatial economic activities and interventions, [6], the Autocorrelation (ISA), which uses Moran’s I delta is potentially subjected to natural hazards measure to test for spatial autocorrelation across including the earthquakes and probability of a series of distances throughout a study area, Tsunami. was conducted to determine the distance

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

associated with peak clustering of vulnerability mapping on a national and sub- correlation between the analyzed seismic regional level. values. The value obtained from ISA was then used as distance threshold or radius for 2. STUDY AREA determining proximity weights for calculating Moran’s I, [10]. The spatial econometrician which The study area occupies the Egyptian northern estimating the spatial autocorrelation coast from Assalloum at the far west to Rafah at coefficient of regression method are usual the far-east and extends about 40 km southward approaches, [11]. from the coastline, with a total area of about 7700 km2. The area is marked by the Suez Canal at Therefore, this study primarily explores the the east by and the Sinai Peninsula, from the potentiality of the current and projected west by the western desert, from the south by risks of earthquakes. This research anticipates the rest of the agricultural land of the Nile delta providing baseline information of the expected and by the Mediterranean Sea from the north geotectonic hazards along the valuable hotspots (Fig. 1). It includes big cities along the coast such and highly sensitive northern coastal zone of as Matrouh and Alexandria to the west; Port Egypt (Mediterranean coast). Priorities will Saeid, Al Arish and Rafah to the East and in the include threats of, regional and national hazards middle there are Damietta, Ras Albar, Baltim and of earthquakes, geological structures and faults Rosetta cities. The study area governed by 8 and the susceptibility for catastrophic local governorates, which are; from the east to phenomenon such as tsunami. It is anticipated the west; north Sinai, Port Said, Al Dakahlia, that the outcomes of this research would 1) Damietta, Kafr El-Shiekh, El-Beheira, Alexandria, explore the relationships between the reported and Matrouh. The climatic condition of this area seismic points within the study area based on the is almost the climate of the Mediterranean Sea geo-statistical models, 2) enhance our with minimum temperature of 10˚ C in winter and understanding of the relationship between the maximum temperature of 40˚ C in summer. The tectonic plates sheer zones and the seismic area is characterized by different natural activities that generates the extreme geotectonic landforms such as sand dunes, beaches, hazards, and 3) support developing hazards and wetlands, and salt marshes.

Fig. 1. Area of study of the northern coastal zone of Egypt with the major land covers features and socio-economic activities

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

The Mediterranean Sea is an active basin with along the northern Africa coasts. The result of earthquakes particularly in the area of tectonic edge waves, a significant energy is trapped and plates; where the African plate is drifting in north carried along the coast of Egypt. direction to collide with European plates, [12]. This region is associated with numerous seismic Therefore, Egypt is considered as a country of activities of shallow and intermediate depth. low to moderate vulnerability to seismic hazard, However, to the east of Egypt where the Red [14]. Within the boundary of its territory, it is Sea rift lies, which is a zone of plate separation affected by the active tectonic structures of the along Sea-floor that has the forces pushes the rift valley of the Red Sea, Gulf of Suez and Gulf African and Arabian plates apart. The zone is of Aqaba and other active faults within the associated with shallow seismicity. The western country. Regionally, comparing the seismicity in side of Egypt is merely part of the African plate Egypt with the large-scale tectonic features; it is that is relatively stable with no major earthquake recognized that two main seismic dislocation risk. zones are bounding Egypt, 1) the Red Sea - Gulf of Suez due to NNW faults, and 2) Egypt - The southern Italian coastal zone, western of our Mediterranean coastal dislocation zone due to study area, has been studied by Lorito et al. [13]. deep E-W faults, [15]. These faults are They estimated tsunami scenarios sources like as responsible for some significant seismic activities the large Hellenic Arc earthquake that might and create major threat. produce a much higher tsunami wave (up to 5 m) than those of the other source zones (up to 1.5 The focus in this research is on two main m). This implies that tsunami scenarios for hazards sources that anticipated to potentially Mediterranean Sea countries must necessarily create major threat on the coastal zone of Egypt, be computed at the scale of the entire basin, 1) Geo-tectonics (earthquakes and tsunami), and (Fig. 2). The tsunami waves higher than 1 m 2) Land subsidence (submergence and (more than 5 m at some places) are predicted emergence).

Fig. 2. Tectonic sketch map of Mediterranean basin, [13] Instrumental seismicity (yellow dots; M > 4; depth 0–50 km) is taken from the ISC Catalogue (ISC, 2004). Color- shaded ribbons highlight the main structures capable of generating tsunamis that pose significant hazard to Mediterranean shore-facing settlements (shown in blue or red. Those shown in red have been investigated in this work). Selected earthquakes are shown with circles: 1) El Asnam, 1980; 2) Boumerdes, 2003; 3) Crete, 365 AD; 4) Palermo, 2002; 5) Northern Sicily, 1823; 6) Messina Straits, 1908.

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

3. MATERIALS AND METHODS into weighted features. Using the distribution of the weighted features, the The data for this research were collected from tool will identify an appropriate scale of various sources. The historical earthquakes data analysis. collected from the national Egyptian seismic network and USGS global earthquakes network. Since the Optimized Hot Spot Analysis tool uses In addition, the geological maps, land use and the average and the median nearest neighbor land cover maps, satellite images and census calculations for aggregation and also to identify data. All these data are registered into GIS an appropriate scale of analysis, the Initial Data platform to enable spatial analysis and mapping. Assessment component of the tool will also Basic and advanced GIS data processing was identify any locational outliers in the Input adopted to enable for generating the required Features or Polygons For Aggregating Incidents maps as follow: Into Points and will report the number it encounters. To do this, the tool computes each 1- Earthquakes data, as point features, with feature's average nearest neighbor distance and attributes of their magnitude, depth, and evaluates the distribution of all of these frequency have reached to 3083 points distances. Features that are more than a three dated from 1951 to 2015. standard deviation distance away from their 2- Tectonic plates, as either line or polygon closest non-coincident neighbor are considered features, with attribute of their name and locational outliers. description, which used to spatially analyze their influence on the tectonic settings and The statistical significance of the output features relation to the earthquakes within the study will be automatically adjusted for multiple testing area. and spatial dependence using the False 3- Land cover classes, as polygon features, Discovery Rate (FDR) correction method. Also, that generated from classified satellite the output features will reflect the aggregated data, and used for spatial correlation with weighted features (fishnet polygon cells, the hazardous zones and estimate the natural aggregation polygons you provided for the hazards impacts on the socio-economic Polygons for Aggregating Incidents into points resources within the study area. parameter, or weighted points). Each feature will 4- Population densities per the Egyptian have a z-score, p-value, and Gi_Bin result, [16]. governorates to estimate the damages and losses. The output of this module is classified as – cold spot confidence (99, 95, and 90%) and the hot In this context, we used different modules of the spot confidence (90, 95, and 99%). ArcGIS Desktop 10.2 Software for data processing, analysis and mapping of the b. The data is also processed by the gathered data, as follow: module “Spatial Statistics Tools / Rendering / Cluster/Outlier Analysis with 1- The ArcMap module used for data entry Rendering”. The Cluster and Outlier and editing to integrate all the collected Analysis tool identifies spatial clusters of seismic data in one layer. features with high or low values and 2- The earthquakes’ points were processed spatial outliers. To do this, the tool and analyzed by the ArcGIS modules as calculates a local Moran's “I” value, a z- follow: score, a p-value, and a code a. The First Module is The Spatial representing the cluster type for each Statistical Tools / Mapping clusters / statistically significant feature. The z- Optimized Hot Spot Analysis. This scores and p-values represent the module executes the Optimized Hot Spot statistical significance of the computed Analysis (Getis-Ord Gi*) tool using index values. Positive values for “I” parameters derived from characteristics indicates that a feature has neighboring of the earthquakes’ magnitudes as features with similarly high or low incident points. It interrogates the data to attribute values; this feature is part of a obtain the settings that will yield optimal cluster. A negative value for “I” indicates hot spot results. If, for example, the Input that a feature has neighboring features Features dataset contains incident point with dissimilar values; this feature is an data, the tool will aggregate the incidents outlier. In either instance, the p-value for

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

the feature must be small enough for the parameter introduces bias in order to stabilize cluster or outlier to be considered the predictions, the ridge parameter should be as statistically significant. The output small as possible while still maintaining model cluster/outlier type (COType) field stability, [16]. distinguishes between a statistically significant cluster of high values (HH), This module uses the locations of earthquakes’ cluster of low values (LL), outlier in which magnitudes as points and the lines of tectonic a high value is surrounded primarily by plates as input layers to find a kind of relation low values (HL), and outlier in which a between the intensity/magnitude values with the low value is surrounded primarily by high tectonic plates sheer zones. values (LH). Statistical significance is set at the 95 percent confidence level. When 3- The ArcMap module is used also for no FDR correction is applied, features mapping the outputs of the processed with p-values smaller than 0.05 are data. considered statistically significant. The FDR correction reduces this p-value 4. RESULTS AND DISCUSSION threshold from 0.05 to a value that better reflects the 95 percent confidence level 4.1 Vulnerability to Geotectonic Hazards given multiple testing. Egypt is located in the southeastern part of the The Cluster/Outlier Analysis with Rendering tool Mediterranean Sea, and represents a combines the Clusters and Outlier Analysis and subordinate part of the Eastern Mediterranean ZScore Rendering tools in a model. It gives a set region, which is a small ocean basin known by its of weighted features, identifies hot spots, cold unusual tectonic complexity. It includes a spots, and spatial outliers using the Anselin Local short segment of the convergence boundary Moran's I statistic. Then, it applies cold-to-hot between Africa and Eurasia creating northward rendering to the z-score results, [16]. movement of the African Plate relative to the Eurasian Plate, [17-19]. Subduction in this c. The third module is the Geo-statistical segment is along two very small arcs, the Analysis Tools / Interpolation / Kernel Hellenic and Cyprean arcs. The risk of Interpolation with Barriers. The Kernel earthquakes is anticipated to be at highest level Interpolation is a variant of a first-order in the Egyptian Delta region due to the dense Local Polynomial Interpolation in which concentration of population and human economic instability in the calculations is prevented development, [12]. using a method similar to the one used in the ridge regression to estimate the Locally, Sinai triple junction region, which occur regression coefficients. When the in a NW trend closely parallel to the Gulf of Suez, estimate has only a small bias and is is characterized by intense seismicity associated much more precise than an unbiased with complex tectonic activity of three plates. The estimator, it may well be the preferred total reported earthquakes during the same time estimator. The Kernel Interpolation span are about 52 events with a maximum model uses the shortest distance magnitude of 6.3 and about 49 events with between points so that points on the minimum magnitude of 3.1 and maximum of 5.9 sides of the specified nontransparent Richter scale, [20,21]. (absolute) barrier are connected by a series of straight lines. Unfortunately, most of the well recorded earthquakes are land sources, with no insights The Local Polynomial Interpolation prediction on the marine large number of earthquakes error is estimated assuming that the model is reported from the Mediterranean Basin. The correct. This assumption is often violated and the Arabian-Agean Plates are significantly spatial condition number highlights areas where contributed to these earthquakes that might the predictions and prediction standard errors are create Tsunami. Two old incidents of Tsunami unstable. In the Kernel Smoothing model, the were recorded in Egypt due to these tectonic problem with unduly large prediction standard plates, which were in the years 320 and 1303 errors and questionable predictions is corrected and caused severe damage to Alexandria, [22] with the ridge parameter by introducing a small and [23]. The event of the year 320 was very amount of bias to the equations. Since the ridge destructive that destroyed more than 50,000

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

houses (one third of the city) and killed 5,000 these earthquakes are located in the marine. In people in Alexandria, [24]. addition, Aegean and Anatolia shear zones is the highest contributor of the earthquakes with nearly To evaluate the magnitude of geotectonic 43% and 42% respectively. However the least hazards from marine earthquakes that might one is the Arabia zone with 1%, and Africa is create Tsunami, it is important to map the about 14%, (Table 1). location of earthquakes in relation to the plates’ zones and the coastal zone of Egypt as well. The shallower earthquakes' activities in the (Fig. 3) shows the spatial distribution of both land Hellenic arc are higher frequency than in the and marine earthquakes since 1951 till 2015 in Cyprean arc, which extends from Albania in the the Mediterranean Basin in relation to the geo- west to southwestern Turkey in the east. About tectonic shear zones. It was found that 85% of 85% of the earthquakes epicenters were less

Fig. 3. Spatial distribution of the earthquakes points (1951-2015) and the tectonic plates along the coastal and marine of the study area

Table 1. Statistics of the earthquakes and the tectonic plates within the Mediterranean

Source Number % Tectonic Zone Number % Marine 2618 85% Aegean Sea 1321 43 Land Anatolia 1297 42 465 15% Africa 442 14 Arabia 23 1 Total 3083 100% 3083 100

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

than or equal 40 kilometers beneath the sea I), Cluster and Outlier Analysis (Anselin Local floor, whereas nearly one third of the analyzed Moran’s I), and Hot Spot Analysis (Getis-Ord Gi). earthquakes depths were less than or equal 10 A positive value for I indicate that a feature has kilometers, Table 2. These activities are neighboring features with similarly high or low mostly seaward that are potential for creating attributes values; this feature is part of a cluster. Tsunami, Fig. 4. Moreover the southern part of A negative value for I indicates that a feature has the Aegean Sea is moving as a relatively neighboring features with dissimilar values; this rigid block compared with the surrounding zones, feature is an outlier. However, the positive results [25]. of Moran’s I statistic with significant p-values and high Z-scores indicate spatially clustered data Table 2. Summary Statistics of the analyzed sets. At the same time, negative Moran’s I Earthquakes Depths depicts that the spatial pattern is more spatially dispersed [26; 27]. Depth (meters) Earthquakes No. % 0 - 10 844 27.38 The Spatial Autocorrelation (Global Moran’s I) 11 - 20 356 11.55 tool measures spatial autocorrelation based on 21 - 30 575 18.65 both feature locations and feature values 31 - 40 828 26.86 simultaneously. Given a set of features and an 41 - 50 136 4.41 associated attribute, it evaluates whether the 51 - 191 344 11.16 pattern expressed is clustered, dispersed, or Total 3083 100 random [27]. The Spatial Autocorrelation (Global Moran’s I) was used in relation to the correlated Several statistics in the Spatial Statistics toolbox points where the seismic points as the current are inferential spatial pattern analysis techniques study. including Spatial Autocorrelation (Global Moran’s

Fig. 4. The depths anomalies of the earthquakes within the tectonic plates

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

To map the clusters by the spatial statistical result of optimized hot spot analysis and tools, the Gets-Ord Gi* analysis on the approves the same findings. distribution of the earthquakes' magnitudes, it optimized hot spot areas that clearly show the In this context, we try to find a relation between highest number and effectiveness of earthquakes the seismic activities and the sheer zones of the are located at the Aegean Sea plate. The named tectonic plates, ridges and trenches, a majorities of the hot spotted earthquakes are kernel interpolation with barriers of the geo- spatially concentrated within the Aegean Sea statistical analysis tools module was used. The plate and to the southern margin of the higher magnitudes of earthquakes (considered to Mediterranean ridge, while the majority of the >=3.9 in Richter scale) were dominated to the cold spotted ones are at the Anatolia Plate, western side of the African plate especially at the (Fig. 5). Agean Sea and Asian-African sheer zone and to the south of the Mediterranean Ridge and In addition, throughout the statistical analysis of southeast of the Arabian-Asian sheer zone. It is the optimized hot spot of the Gi* values, the hot extremely the same conclusion of the above spot points (90, 95 and 99%) calculated as 44% analyses, the high-high clusters and high-low of the total processed points were 3083, (Table outliers of the Cluster-Outlier Analysis with 3). Based on the distributions of these Rendering and the hot spots of the optimized hot values, this explains that the earthquakes at the spot analysis. Therefore, the potentiality of the Aegean Sea plate and the areas along the frequent and massive earthquakes and tsunami Mediterranean ridge are might potential source phenomena might happen at the mentioned of the massive and frequent shakes and zones, (Fig. 7). tsunamis. 4.2 Land Subsidence – Submergence High/low clustering (Getis-Ord Gi) or cluster- outlier analysis (Anselin Local Moran's I) The Nile Delta is geologically created as a deep statistics; the term hot spot has become an graben that filled with thick column of clay and integral part of the study called data analysis and fine sediments. Few researches recognized the is popular with most of the analyst. A hot spot as difference in the land subsidence along the Nile the name suggests is a state of indicating some Delta coast founding that the eastern region is subjects of clusters in a spatial distribution higher than the west. They also anticipated that [28;29]. The cluster/outlier type field the land subsidence in the Nile Delta is due to distinguishes between a statistically significant the compaction of sediments. The difference of cluster of high values (HH), cluster of low values the land subsidence rates of the northern Nile (LL), outlier in which a high value is surrounded delta is not only referred to the sediments' primarily by low values (HL), and outlier in which compaction that stated by Stanley and Warne a low value is surrounded primarily by high [32]; and Frihy [33], but also it may be varied due values (LH). Statistical significance is set at the to the differential rates of the African plate 95 percent confidence level. For statistically northward movements from the west to the east. significant positive z-scores, the larger the z- This variation is previously stated by Stanley [34] score, the more intense the clustering of high and Stanley [35] due to differential compaction values (hot spot) [30;31]. and varying thicknesses in the Holocene layers. Stanley and Clemente [36] summarizes the land Therefore, when applying the Cluster-Outlier subsidence rate of the Nile delta coastal zone as Analysis with Rendering which uses the Anselin about 3.7 mm/yr in the NW delta, about 7.7 Local Moran's I statistics, it shows that the high- mm/yr in the N delta, and about 8.4 mm/yr in the high clusters and low-high outliers spots (low NE delta, based on compaction rates of earthquakes surrounded by high ones) are Holocene sediments' thicknesses which dominated at the Agean Sea plate. While, the decreases from the east to the west. high-low outlier spots (high earthquakes surrounded by low ones) and low-low cluster Furthermore, to the east and based on age-dated spots are dominated at the Anatolia Plate, (Fig. sediment core sections, [32] and [35] have 6). Throughout the statistical analysis of the estimated long-term average subsidence rates cluster-outlier analysis with rendering result, the across the Nile delta region. The processes of high-high clusters and high-low outliers’ sums to compaction and dewatering of the thick 44% of the total analyzed points were 3083, accumulated deposits of fluvio-marine deltaic (Table 4). This result is extremely similar to the mud sequence formed in the Holocene have

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

induced higher rates of subsidence ranging from mm/yr further to the west, where the deltaic plain 5 mm/yr at Port Said in the east, where the thickness is decreased or nearly absent below deltaic plain thickness is about 50 meter, to 1 Alexandria coastal plain, [32,37], (Fig. 8).

Table 3. Summary of the Optimized Hot Spot Analysis (Getis-Ord Gi*)

Optimized Hot Spot Analysis (Getis-Ord Gi*) Gi_Bin Count Gi_Bin % Cold Spot - 99% Confidence -3 1148 37.24 Cold Spot - 95% Confidence -2 52 1.69 Cold Spot - 90% Confidence -1 13 0.42 Not Significant 0 486 15.76 Hot Spot - 90% Confidence 1 96 3.11 Hot Spot - 95% Confidence 2 187 6.07 Hot Spot - 99% Confidence 3 1101 35.71 Total 3083 100

Table 4. Summary of the Cluster_Outlier Analysis with Rendering

Cluster/Outlier with Rendering Count COType % Not Significant 589 19.10 High-High 1035 33.57 High-Low 342 11.09 Low-High 140 4.54 Low-Low 977 31.69 Total 3083 100

Fig. 5. Spatial statistical mapping of the earthquakes’ magnitudes by Hot Spot Analysis (Gets-Ord Gi*)

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

Fig. 6. Spatial statistical mapping of the earthquakes by Cluster-Outlier Analysis with Rendering

Fig. 7. Kernel interpolation of the earthquakes’ magnitudes with barriers of plate tectonics’ sheer zones

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

Fig. 8. Spatial distribution of land subsidence rates in the northern delta Source: modified from [21]

Fig. 9. Expected directions of the plate tectonics’ movements within the study area

The variability of emergence and subsidence of Canopus (500 BC) in Abu Quir Bay was originally Alexandria land (ranging between –5 mm and +7 located 3 m above sea level, which may imply mm per year) as calculated by Warne and that it has submerged of 8 m during the past Stanley [38] may be attributed to the impact of 2,500 years. tectonic activities. Tectonic activities in Alexandria have been recorded from the To summarize this, we founds that the driving observations on submerged Roman and Greek forces influence the subsidence of the Nile delta ruins in the Eastern harbor and Abu Quir Bay, as coastal zone is varied from the west, where the old as 2,500 years had submerged from 2 to 5.5 geo-tectonic-controlled, to the east, where the m, [38] and [39]. Therefore, the Hellenistic city of delta sediments compaction. We propose that

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

land subsidence is not only due to the Sea due to the named ridges/trenches compaction of the Nile delta grapen's sediments which make the frequency and severity of (if this is the case the rate of the subsidence earthquakes than that of Anatolia plate. should be similar along the Nile Delta), it is This makes the northward movement rate driven by geo-tectonics. The differential towards the Aegean-African plate is a bit movement of the African plate is also generates lower due to named ridges/trenches the differential sea waves and tidal gauges as making a resistance to the African plate well. In this case, the sea level rise potentiality is northward subduction than that to the a result of the subduction movements of the eastern Mediterranean side where only the African, Agean and Arabian tectonic plates. This Cyprus trench exists. align with [40,41], where the structure framework 2. The subsidence rates aligned to the rates controlling the vertical motion due to the of the tectonic plates’ movement in geodynamic setting including earthquakes addition to the coastal deltaic sediments epicenters and major active fault trends were compaction. This was aligned with the detected at the north western Nile delta. The results from the kernel interpolation of the structural pattern results from a complex seismic points and their relations with the interplay of fault trends of the N-S faults (Abu boundaries of the plates’ sheer zones. Quir), NE faults (Rosetta), NW Suez-Cairo- 3. As the result of the cluster-outlier analysis Alexandria line, and NE-SW (Qattara- with rendering, there are about 44% of Eratosthenes line). These structural trends High-High and High-Low relations. This indicate that the main cause of subsidence proves that some of the points may in the western Nile delta is ongoing faulting, as generated/accelerated the most severe well as down warping, of the underlying 3000 earthquakes due to geospatial statistical meters of Late Miocene to Quaternary relations that happened between the H-H sequences. and H-L seismic points. This also approved by the hot spot analysis that results about In addition, the depths of the majority 44% of the sum the hot spot (90-95-99%) earthquakes epicenters (85%) were above 40 confidence points. kilometers from the sea floor, one third of them were down to 10 kilometers depth. (Fig. 9) COMPETING INTERESTS summarizes the predicted directions of the plate tectonic movements based on the geospatial Authors have declared that no competing analysis and findings of this research. At the interests exist. African plate, the movement of the eastern side is increased northward along the Arabian-African REFERENCES sheer zone (at eastern Nile delta and Sinai).

Also, the movement of the western side of the 1. Milliman JD, Qin YS, Park YA. Sediment African plate is north-northeast at the western and sedimentary processes in the Yellow desert of Egypt while it is skewed to the north- and East China Seas A. Taira, F. Masuda northwest along the eastern coastal zone of the (Eds.), Sedimentary Facies in the Active Nile delta. This makes the movement along the Plate MarginTerra Scientific, Tokyo. 1989; eastern coastal zone is higher than the western 233–249. coastal zone of the Nile delta. 2. Syvitski JPM, Saito Y. Morphodyna-mics of

5. CONCLUSION deltas under the influence of humans Global Planet. Changes. 2007;57:261– Geo-spatial and statistical analysis found to be a 282. potential tool to show off the spatial relation 3. Gavin Hayes & Tony Crone, United States between the seismic activities and the tectonic Geological Survey (USGS). plates within the area of study. The Egyptian Available:https://www.usgs.gov/faqs/what- coast that is a part of the African plate and depth-do-earthquakes-occur-what- extended to the Aegean plate is dissected by the significance-depth?qt- Mediterranean Ridge, Strabo Trench and Pliny news_science_products=0#qt- news_science_products trench. There are three predicted scenarios: th (26 Sep. 2018) 1. The majority of the hot spotted 4. Petrishchevsky M. The relation of earthquakes are located at the Aegean seismicity to lithospheric density inhomogeneities in the Russian Far East,

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

Journal of Volcanology and Seismology. trench near Crete. Geophysics. Journal Int. 2007;1(6):410–420. 1990;102:695–731. 5. Munich Re. Topics geo annual review: 19. Abou Elenean K. Seismotectonics of the Natural catastrophes 2006. Geo Risks Mediterranean region north of Egypt and Research. Munich Re Group, Munich; Libya, M. Sc. Thesis. Fac. of Sci., 2006. Mansoura Univ., Egypt. 1993; 198. 6. Abou El-Magd I, Hermas EA. Human 20. Badawy A. Earthquake hazard analysis in impact on the coastal landforms in the area northern Egypt Acta Geod. Geophys. between gamasa and kitchner drains, Hung. 1998;33:341–357. Northern Nile Delta, Egypt J. Coastal Res. 21. Badawy A, Al-Gabry M, Girgis M. Historical 2010;26(3):541–548. seismicity of Egypt. In: A Study for 7. Getis A, Ord JK. The analysis of spatial Previous Catalogues Producing Revised association by use of distance statistics. Weighted Catalogue the Second Arab Geographical Analysis. 1992;24(3):189– Conference for Astronomy and 206. Geophysics, Egypt; 2010. 8. Wong DWS, Lee J. Statistical analysis of 22. Ambraseys NN, Melville CP, Adams RD. geographic information with ArcView GIS The seismicity of Egypt, Arabia and the and ArcGIS. John Wiley & Sons, Hoboken, Red Sea. Cambridge University Press, NJ, USA; 2005. Cambridge. 1994;182. 9. O’Sullivan D, Unwin DJ. Geographic 23. El-Sayed A, Vaccari F, PANZA G. information analysis. John Wiley & Sons; Deterministic seismic hazard in Egypt, 2003. Geophys. J. Internat. 2001;14:555–567. 10. ESRI. Spatial Statistics Tools, ArcMap 24. El-Sayed A, Korrat I, Hussein HM. 10.1. ESRI, Redlands, California; 2012. Seismicity and seismic hazard in 11. Anselin L. Spatial econometrics: Methods Alexandria (Egypt) and its surroundings. and models. Dordrecht: Kluwer; 1988. Pure appl. Geophysics. 2004;161:1003– 12. Degg MR, Doornkamp A. Earthquake 1019. hazards atlas, 2 - Egypt based on the R. DOI: 10.1007/s00024-003-2488-8. O. An Earthquake hazard zonation scheme 25. McKenzie D. Some remarks on the R. O. A Reinsurance Office Association development of sedimentary basins. Earth Aldernary House, Queen Street, London and Planet Science Letters. 1978;40:25– EC 4N 1ST, United Kingdom, P- CL; 2.1. - 32. C 1. 2.24; 1990. 26. Luković J, Blagojevć D, Kilibarda M, Bajat 13. Lorito S, Tiberti MM, Basili R, Piatanesi A, B. Spatial pattern of North Atlantic Valensise G. Earthquake-generated oscillation impact on rainfall in Serbia. tsunamis in the Mediterranean Sea: Spatial Statistics Journal. 2015;14:39–52. Scenarios of potential threats to Southern Available:http://dx.doi.org/10.1016/j.spasta. Italy. J. Geophysical. Research. 2008;113: 2015.04.007 B01301. 27. ESRI, Spatial statistics tools, ArcMap 10.3. DOI: 10.1029/2007JB004943 ESRI, Redlands, California. ESRI, ArcMap 14. EI-Sayed AR, Wahlstrom Kulhanek O. 10.3. ESRI, Redlands, California; 2014. Seismic hazard of Egypt. Natural Hazards. 28. Ansari SM., Kale K. Methods for crime 1994;10:247-260. analysis using GIS. ESRI; 2014. 15. Maamoun ME, Ibrahim EM. Tectonic Available:www.esri.com/publicsafety activity in Egypt as indicated by 29. ESRI. The use of ArcGIS Geostatistical earthquakes. Acadmy of Scientific analyst exploratory spatial data analysis. Research and Technology, Helwan (Accessed 20th Dec. 2018) Institute of Astronomy and Geophysics. Available:http://dusk2.geo.orst.edu/gis/geo 1978;Bull No. 170:20. stat_analyst.pdf 16. Esri, ArcGIS Desktop 10.2 Help. 30. Zhou W, Minnick MD, Mattson ED, Geza 17. Rabinowitz P. and Ryan W. Gravity M, Murray KE: GIS-based geospatial anomalies and crustal shortening in the infrastructure of water resource Eastern Mediterranean. Tectonophysics. assessment for supporting oil shale 1970;5–6:585– 608. development in Piceance Basin of 18. Taymaz T, Jackson J, Westaway R. Northwestern Colorado. Computers & Earthquake mechanism in the Hellenic Geosci. 2015;77:44-53.

Amasha et al.; PSIJ, 20(3): 1-15, 2018; Article no.PSIJ.46208

31. Mahboubi P, Parkes M, Stephen C, Chan Available:http://dx.doi:10.1130/GSATG312 HM. Using expert informed GIS to locate A.1. important marine social-ecological 37. Chen Z, Warne AG, Stanley DJ Late hotspots. Journal of Environmental Quaternary evolution of the northwest Nile Management. 2015;160:342-352. delta between Rosetta and Alexandria, Available:http://dx.doi.org/10.1016/j.jenvma Egypt. J. Coastal Research. 1992;8:527– n.2015.03.055 561. 32. Stanley DJ, Warne AG. Nile Delta: Recent 38. Warne AG, Stanley DJ. Late quaternary geological evolution and human impact. evolution of the North West Nile delta and Science, New Series. 1993;260(5108):628- adjacent coast in the Alexandria region 634. Egypt”, Journal of Coastal Research. Available:https://www.jstor.org/stable/2881 1993;9:26-64. 247 39. El Sayed MKh Sea level rise in Alexandria 33. Frihy OF. The Nile delta-Alexandria coast: during the late Holocene: archaeological Vulnerability to Sea-level rise, conse- evidences. Rapp Comm Int Mer quences and adaptation. Mitigation and Me´diterrane´e; 1988. Adaptation Strategies for Global Change. 40. Garziglia S, Migeon S, Ducassou E, 2003;8(2):115-138. Loncke L, Mascle J. Mass-transport 34. Stanley DJ. Subsidence in the deposits on the Rosetta province (NW Nile northeastern Nile delta: Rapid rates, deep-sea turbidity system, Egyptian possible causes, and consequences. margin): Characteristics, distribution, and Science. 1988;240:497-500. potential causal processes. Marine 35. Stanley DJ. Recent subsidence and Geology. 2008;250:180–198. northeast tilting of the Nile delta, Available:http://dx.doi.org/10.1016/j.marge Egypt", Marine Geology. 1990;94(1– o.2008.01.016 2):147–154. 41. Zaghloul ZA, Elgamal MM, El Araby H, Available:http://dx.doi:10.1016/0025- Abdel Wahab W. Evidences of neo- 3227(90)90108-V tectonics and ground motions in the 36. Stanley DJ, Clemente PL. Increased northern Nile Delta’, in Z.M. Zaghloul’ and land subsidence and sea-level rise M.M. Elgamal (eds.), Deltas-Modern and are submerging Egypt's Nile Delta Ancient, Egypt, proceedings of Mansoura Coastal Margin"; GSA Today. University, First International Symposium 2016;27. on the Deltas. 1999;285–314. ______© 2018 Amasha et al.; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Peer-review history: The peer review history for this paper can be accessed here: http://www.sciencedomain.org/review-history/28142